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https://github.com/esteve/gpt

gpt
https://github.com/esteve/gpt

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gpt

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README 

        
This a binary code release of GPT for LINUX/INTEL architecture.

It has been tested on Red Hat Linux 6.0.



This is a BETA version. Documentation about GPT can be found 

in this file and in the docs directory of this distribution.



GENERAL PLANNING TOOL

=====================



GPT is a planner for problems involving partial information

and uncertainty. Such problems can be divided in three types:

conformant, contingent and probabilistic contingent (see the

paper ijcai2001.pdf paper in the docs directory). The input

to GPT is a planning problem encoded in an extension of the

PDDL language that supports uncertainty and incomplete

information. Depending on problem type, the algorithm is either

a best first search in belief space or real-time dynamic programming.

In any case, the solver is guided by an heuristic function

that is automatically extracted from the problem representation.



LICENSE

=======



This is a research/teaching only license. It cannot be used

for commercial purposes without the consent from the authors.



REQUIREMENTS

============



In order to use GPT you will need the GNU C/C++ g++ compiler

and some standard unix tools like: make, ld, ...

Be sure they are in your path before running GPT.



*** NOTE: THIS DISTRIBUTION *WILL* NOT WORK WITH OTHER C/C++ COMPILER ***



INSTALLATION

============



1) unpack distribution files, for example



    $ gzip -dc gpt--linux-binary.tar.gz | tar -xvpf -



2) clean and generate necessary files



    $ make -f Makefile.linux clean

    $ make -f Makefile.linux compile



3) set the var GPTHOME to the gpt directory, for example (using ksh/bash)



    $ export GPTHOME=`pwd`/gpt--linux-binary



RUNNING SOME SAMPLES

==================== 



The sample problems are in the example directories. 

Here is an example for solving some of them:



1. Conformant Planning:



   - change to the bombing the toilet problem directory, 



     $ cd $GPTHOME/examples/aips-paper/bombing/bt



   - solve a problem using the gpt script,



     $ $GPTHOME/bin/gpt < script.gpt



   - see the result



     $ cat p6_bt.output



2. Contingent Planning:



   - change to the medical problem directory,



     $ cd $GPTHOME/examples/aips-paper/medical



   - solve a problem using the gpt script,



     $ $GPTHOME/bin/gpt < script.gpt



   - see the graph version of the optimal policy,



     $ $GPTHOME/bin/viewer p5.gml 



3. Probabilistic Contingent Planning:



   - change to the omelette problem directory,



     $ cd $GPTHOME/examples/aips-paper/omelette



   - solve a problem using the gpt script,



     $ $GPTHOME/bin/gpt < script.gpt



   - see the graph version of the optimal policy,



     $ $GPTHOME/bin/viewer p2.gml



THE GPT SHELL

=============



The main difference between the current release and previous ones

is the GPT shell. In this new release, all necessary steps to solve

a problem (a .pddl file) are performed inside the gpt shell. Such steps

are: parse the .pddl file to generate a C++ version of the problem, 

compile the problem using the C/C++ compiler, solve the problem, and

generate a representation of the resulting policy. The representation

can be either policy graph, a policy table, or, in the case of conformant

planning, a sequence of actions. For more information, use the help command

in the gpt shell and check the examples.



POLICY GRAPH

============



The policy graph is a labeled directed graph in which the nodes represent

states of the controller (system states for planning with complete

information and belief states for planning with partial information),

and the edges represents the transition dynamics for the current policy.

The label attached to a node is the name action given by the policy 

in that node. The different outgoing edges represent the next controller

states for that state/action under the different feedbacks.

The nodes are also colored as cyan, red or yellow. The cyan color

indicates the initial states and the yellow color the goal states.

The other states are colored red. 



The graph output is in the GML format supported by the LEDA project.

We have included a graph viewer (a LEDA program) inside GPT that can be

invoked from inside the GPT shell with the command 'viewer' or from the UNIX 

shell with $GPTHOME/bin/viewer. Initially, the graph will look odd since the

nodes are positioned at random. However, you can get a nice drawing

of the graph using the "Layout/Spring Layouts/2D Spring Embedder" function.

In the future, we expect to improve the viewer with functionality for

inspecting/revealing information about the states, actions, and observations

in the policy graph.



STOPPING RULE

=============



Another important difference of the current release is the implementation

of GPT's stopping rule for finishing the Real-Time Dynamic Programming

trials once the optimal policy has been computed. Thus, the user can

instruct the solver to compute the optimal policy for a given planning

problem. This is the default option in GPT. See the ijcai2001-ws.pdf 

file in the docs directory for more information.



We hope you find GPT an useful tool either for research, teaching or both.

If you have any question or comment, please do not hesitate to contact us.



Sincerely,



Blai Bonet         [email protected], [email protected]

Hector Geffner     [email protected]